/Machine-Learning-Techniques

This repo has my code which i practiced in my ML lab during my even sem of my 3rd year college

Primary LanguageJupyter NotebookBSD 3-Clause "New" or "Revised" LicenseBSD-3-Clause

Machine Learning Techniques Repository

Welcome to the Machine Learning Techniques Repository! This repository contains implementations of various machine learning algorithms and techniques that I have developed during my third year in college as part of my machine learning lab projects.

Table of Contents

  1. Introduction
  2. Algorithms Implemented
  3. Usage
  4. Contributing
  5. License

Introduction

This repository serves as a collection of machine learning algorithms and techniques that I've implemented as part of my coursework during my third year in college. The implementations are coded in Python using libraries such as NumPy, scikit-learn, TensorFlow, and PyTorch.

Algorithms Implemented

  • Linear Regression
  • Logistic Regression
  • Decision Trees
  • Random Forests
  • Support Vector Machines (SVM)
  • K-Nearest Neighbors (KNN)
  • Principal Component Analysis (PCA)
  • Llinear Discriminant Analysis (LDA)
  • Feed Forward NN
  • Convolutional Neural Network
  • Hidden Markov Model

Usage

To use any of the implemented algorithms, follow these steps:

  1. Clone the repository to your local machine:
git clone https://github.com/mudit2004/machine-learning-techniques.git